Reformed Electricity Market With Deep Penetration Of Renewables

The exhaustion of fossil energy and deteriorating environment in recent years have driven us to the cusp of a historic transformation of the global energy consumption from traditional energy to clean and sustainable energy.Renewable generations which are the main impetus of energy struc-ture transformation,can provide low-cost,zero-pollution and sustainable energy supply,thus have caught worldwide attention.However,deep penetration of renewables not only poses challenges to the balance of supply and demand in energy market,but also brings lots of high-frequency fluctu-ations into ancillary market.Nowadays,the imperfect market mechanism restricts the absorption of renewables.This thesis focuses on the electricity market with deep penetration of renewables,plays the incentive role of price,incentives flexible distributed resources to contribute to system operations.Therefore,it has practical significance to encourage the utilization of renewable energy and maintain stable operation of power system.Firstly,we design the market clearing mechanism from the perspective of maintaining the energy market equilibrium.A multi-generator-multi-consumer scenario in a day-ahead electricity market with deep penetration of renewable energy and price-sensitive consumers is considered.Specifically,at the demand side,we adopt an evolutionary game to model the selection behavior of the population of consumers,while at the supply side,the risk cost function that characterizes the randomness of renewable generations is minimized to control the risk of renewables.At last,a distributed algorithm is proposed to obtain the market equilibrium where the market clearing prices are deternmined.In order to deal with the market disruption caused by renewables,we investigate how to assemble distributed micro-storages for ancillary service of power grid.While bids in capacity market must meet the requirement of minimum bidding size and operating duration,the scheduling and operation of flexible micro-storages can be performed in a much short-time scale.We develop a two-folded mechanism that enables distributed micro-storages owned by end-users to participate the wholesale ancillary market through an aggregator.That is,the aggregator will buy capacities from end-users,assemble them and then sell to the ancillary market.We investigate the profit maximization problem of aggregator,then transform it into a mixed quadratic linear program to reduce computational complexity.Finally,the simulation results demonstrate that the proposed model can not only lower the cost but also fully utilize fragmented resources in both volume and time scale.We further study the optimal scheduling for distributed micro-storages.The randomness of real time utilization ratio is summarized by a distribution-free uncertainty set,based on which we formulate a two stage robust optimization problem to specify optimal day-ahead trading and real time operation.Then,we employ a column-and-constraint generation algorithm to obtain an optimal solution.The nu,mber of iterations is proved to be finite.At last,numerical results illustrate the performance of the proposed approach.